Results on precision and F1 score. Furthermore, in Table REF , our xERM\(_{\!P\!C}\)  again achieves competitive recall and high precision (recall: \(70.3\%\)  precision: \(54.2\%\) ) compared to factual model XE that achieves high recall with lower precision (recall: \(71.4\%\)  precision: \(39.9\%\) ), and achieves high recall and precision on few-shot subset (recall: \(66.1\%\)  precision: \(78.1\%\) ) compared to PC [1]} that achieves similar recall with lower precision (recall: \(66.9\%\)  precision: \(73.3\%\) ). As a result, our xERM achieves the highest F1 score on the two datasets.
